1. Field of the Invention
The present invention relates to a data transmission method using compression techniques to optimize the use of available transmission routes.
2. Description of the Prior Art
Various seismic data transmission systems are used to connect local acquisition units to a central station either directly or via intermediate stations having local-unit concentration or control functions of varying complexity. The links can be provided by means of cables, radio links, one or more relays, or a combination of cable and radio links as indicated for example in French Patents 2,720,518, 2,696,839, 2,608,780, 2,599,533, 2,538,561, 2,511,772, or 2,627,652 of the applicant.
French Patent 2,608,70 of the assignee teaches in particular the use of acquisition units provided with two transmission routes, one with a relatively high transmission rate and the other with a passband that can be relatively narrow depending on local availability of transmission frequencies, which are more readily available in the current radio transmission regulatory framework. The seismic data collected in successive cycles are stored in a mass memory in each of the units and transferred intermittently to a central control and recording station. To allow the operator in the central station to check that data acquisition by each of the acquisition units is proceeding normally, partial data transmissions are made, which fit into a transmission route with a relatively narrow passband.
French Patent 2,625,627, also by the assignee, teaches the use of seismic acquisition units provided in particular with specialized means for processing signals which undergo numerous tests.
The present trend, particularly with so-called 3D seismic prospecting methods, is to distribute hundreds or even thousands of seismic receivers over the area to be surveyed, on land, at sea, or in coastal areas, often over several kilometers. The volume of data to be collected and transmitted grows continually. To prevent transmission problems from hampering the progress of seismic systems, the trend is to use data compression methods chosen for compatibility with the requirements of the geophysicists.
Seismic data compression can save a great deal of space in the mass storage modules in local acquisition units and/or local control and concentration stations, and save a great deal of transmission time.
Numerous methods of data compression exist. They can be divided into two major classes, depending on whether or not they involve loss of information, and whether or not alteration in the data after their decompression can be tolerated.
Particularly in geophysics, it is essential for compression losses to be as small as possible because the most: pertinent information is often very small in amplitude and can be isolated from background noise only by digital processing of several traces. Possible losses in accuracy are tolerable only in very particular cases, if the information transmitted is merely for monitoring equipment operation and visualizing the shape of the sampled traces.
Known methods of data compression can be divided into two families: (a) compression methods with no information loss and (b) methods leading to information loss, with the data restored losing some part of the accuracy of the original data.
a) Of the methods in the first family, methods may be cited that are directed at eliminating data redundancy or so-called dictionary methods in which each word is replaced by its index in a reference table; these are most useful when the files to be compressed contain a great deal of redundancy. A method also known as RLE (run-length encoding) is highly suitable for files containing long sequences of identical values.
Statistical coding methods are also known, in which the data are replaced by a code with the same meaning but taking less space. The Huffman coding method for example consists of associating with a datum a code whose length varies with its frequency of occurrence. Arithmetic coding methods represent a variable number of data by a constant quantity of bits.
A known compression technique known as "LPC" (linear predictive coding) is suitable for compressing sound waves. It consists essentially of replacing a signal sample s(t) by a prediction made from p previous samples, assuming that the signal is stationary.
Instead of transmitting the sample s(t), its prediction s (t) is transmitted, namely the prediction coefficients and the residues e(t), namely the difference between the actual value and the prediction made at time t, which on decompression yields the value s(t)=s (t)+e(t) ). If the prediction is correct, the residues are small and take up less space than the initial values s(t). The number of coefficients used to calculate s (t) is generally small and they occupy less space than s(t). The same applies to e(+) which usually has a smaller amplitude than .DELTA.(t).
In the family of compression methods with losses where the objective is to make the best possible model of a signal with a smaller number of bits, the quantification method, for example, may be cited where a piece of information of n bits is represented by another code only on p (p&lt;n) bits, then, upon decompression, these p bits are extended over n bits by shifting, which brings about substantial losses.
According to other methods such as the DCT (discrete cosine transform) method very often used for image compression, the signal is cut up into blocks of fixed sizes, then each of them is modeled by a set of coefficients which do not represent the amplitude of the signal in time but rather its frequency spectrum. Compression appears by eliminating the highest-frequency coefficients.
Other methods based on wavelet transforms are also used, and described for example by:
Bosman, C. et al., Seismic Data Compression Using Wavelet Transforms, 83rd Annual Meeting SEG. PA1 Vetterli, M. et al. Wavelets and Filter Banks, IEEE Transactions on Signal Processing, Vol. 40, No. 9, September 1992; PA1 Coifman, R. et al, Best Adapted Wave Packet Bases, Numerical Algorithms Research Group, Yale University, or PA1 Daubechies, I., Ten Lectures on Wavelets, CBMS-NSF, 1993.
Any given signal is represented in a base of functions that are translated versions (temporal) and dilated versions (frequency) of a wavelet. Representation of the signal by wavelets translates into a set of different coefficients by means of which the signal can be expressed from a wavelet function base. Transmitting the signal is then equivalent to transmitting these coefficients; compressing it is equivalent to expressing it by a smaller set of coefficients.